Field
Aspects of the present innovations relate to computer networking searches, and, more particularly, to associated systems and methods, such as processing search information, providing interactive search results, and search integration.
Description of Related Information
The web has evolved into a rich, multi-media experience, but the process of searching online and associated drawbacks have changed little in the last fifteen years. Search is still primarily text based (captions) with only small thumbnail images (or previews) appearing as a visual search result. Text captions are machine generated and are not a rich or efficient user experience. Also, humans process visual information much faster than we process text, but there is limited visual information in search results. Search engines have tried to remedy this problem by providing “live previews” of the source web pages and presenting them in text and graphical form. Unfortunately, this process is expensive, storage heavy and adds little value for the end user. Further, Internet search results often result in lists of hyperlinks that are not very informative to the searching user.
For example, FIGS. 1 and 2 show exemplary screenshots of prior art search result pages. These prior art examples show how generally, when an end user performs an Internet search, the search engine produces a search results page (also called an “SERP”). The prior art, as shown in FIGS. 1 and 2, contain lists of results with hyperlinks and a sentence or two about each result, 101, and 201. That text, 101, 102, is machine-selected by proprietary algorithms unique to each search engine—as opposed to being curated by humans—and is sometimes a random and not adequate description of the linked page. As such, there is no end-user control of the displayed text.
The selected text is called a “caption” as shown in FIG. 1 at 101, and FIG. 2 at 201. Captions were first used when there was no rich media on the web and, therefore, were only text-based.
Because of this legacy, architecture search results are mostly text-based captions as shown in FIGS. 1 and 2, the way users consume this media is in a limited format—meaning that they can only view search results as one form of media at any given time, such as limited to just video, or just text.
Continuing with FIGS. 1 and 2, the prior art presented results as text, still images or video. There is not a great deal of context to the captions in search results and the presentation of those results is different from every search engine even though each search engine has its own proprietary search algorithms. In order to refine a search in the prior art systems, one must start a search over or hit the “back” button to return to earlier results. Further, searches from mobile devices only compound problems in the prior art. With limited screen real estate, proprietary operating systems, limited bandwidth and a variety of interfaces, such as touch, voice, keyboards—both on screen and physical.
FIGS. 3 and 4 are illustrations of exemplary prior art web page previews. FIGS. 3 and 4 show that even when an entire page is presented as a live preview, 301, 401—as it is with example company SERP, there is not much value added to the user's search. The information is densely packed and the graphics are too small to be useful. Only the general layout of the page is discernible which does little in terms of adding content or context.
Another problem is that search engine results are often inaccurate and imperfect. Text captions do not always accurately represent the content on a site because they lack context and richness. As a result, a search may not be efficient. Users often waste time uncovering the actual context of individual search results.
Currently, companies or website publishers do not have control over how their caption(s) appear within a SERP. The captions are algorithmically machine generated and cannot be curated by the owner of a site.
In sum, there is a need for systems and methods that address the above drawbacks an/or provide other beneficial functionality or advantages to parties involved with search.